Research and development in the field of wideband radar systems has been undertaken for many years. The impetus for this development was rooted in the successful application of high power instrumentation radars for research in ballistic missile defense and satellite surveillance. Current wideband imaging radars provide considerable real-time discrimination and combat identification capability. Advanced signal processing methods have significantly improved the resolution of processed radar return signals, further improving the state-of-the-art in wideband radar technology.
The ability to identify targets and accurately estimate their size and shape is critical to many applications. In one exemplary application involving a potential ballistic missile defense scenario, defensive strategies rely on accurate target identification and size/shape estimation. The primary goal of a defensive radar system is to find the threat target and provide missile guidance to an interceptor so as to destroy the target with a high probability of success. This can be difficult when there are many objects in the radar's field of view, some purposefully designed to fool radar discrimination algorithms. Decoys, for example, may have radar-cross-section (RCS) levels similar to those of the warhead, making robust target selection based on RCS levels, alone, difficult. Narrowband radars usually lack sufficient range resolution to allow a direct measurement of the target's length, although they are generally useful for tracking and coarse motion estimation. Wideband radars permit a much larger suite of target discrimination algorithms to be employed. Real-time range-Doppler imaging and phase-derived range estimation, for example, are possible with today's wideband radar technology. These techniques permit isolation of individual scattering centers, e.g., nosecone and fin edges, into small range-resolution cells providing a means to measure the target's size and shape.
To achieve fine range resolution, field radars utilize coded waveforms with large time-bandwidth products. Wideband "chirp" waveforms are commonly used in practice due to their ease of generation and processing in the radar receiver. By mixing the radar return signals with a replica of the transmitted signal, a baseband signal is produced with frequency components that are proportional to the relative range between scattering centers on the target. The baseband signal is sampled and Fourier-transformed to provide a range-resolved profile of the target. This process is called pulse-compression. Properties of the compressed pulse, such as resolution and sidelobe levels, depend on the extent and shape of the window function applied to the baseband signal samples. The Fourier theory relations define resolution to be inversely proportional to the total signal length. This means that range resolution improves as radar bandwidth increases.
Many field radars operate on these basic wideband principles. The ALCOR C-band radar was developed in 1970 for the purpose of wideband discrimination research. ALCOR utilizes a wideband chirp waveform with a bandwidth of 512 MHz providing ALCOR with a range resolution capability of about 53 cm. Kwajalein's millimeter-wave radar (MMW) can operate at the Ka- and W-bands and is capable of a transmission bandwidth of 2000 MHz, providing an impressive 14 cm range resolution capability.
The United States also operates high-resolution wideband radars on transportable platforms. One example is COBRA JUDY, which uses S-band phased array and X-band dish antenna radars.
The field radars discussed above provide a high degree of range resolution. Because their intended applications are usually very demanding, however, it is often desirable to significantly improve their existing range resolution capabilities: Important target features are often exhibited over a much smaller than conventionally-processed range resolution cell. To improve a radar's range resolution, one can either increase the radar's bandwidth or process the received signals with super-resolution algorithms. Cost and design limitations are major practical drawbacks to increasing a radar's hardware bandwidth. The desire to obtain higher-resolution radar data without incurring tremendous costs motivated development of robust super-resolution algorithms that can be applied to a wide range of real-world data sets.
In 1990, the Lincoln Laboratory of the Massachusetts Institute of Technology developed a super-resolution algorithm to significantly improve the range resolution of processed radar return signals. The algorithm, which is referred to as bandwidth extrapolation (BWE), increases the effective bandwidth of a radar waveform by predicting the target's response at frequencies that lie outside of the measurement bands. In real-world radar applications, BWE typically improves the range resolution of compressed radar pulses by a factor of two or three. Bandwidth extrapolation often provides striking improvements in the quality of wideband radar images. See K. M. Cuomo, "A bandwidth extrapolation technique for improved range resolution of coherent radar data" Technical Report CJP-60 Rev.1, Lincoln Laboratory, MIT, 1992; S. L. Borison, S. B. Bowling and K. M. Cuomo, "Super-resolution methods for wideband radar" Lincoln Laboratory Journal, vol. 5, No. 3, pp 441-461, 1992; the contents of which are incorporated herein by reference.
Bandwidth extrapolation improves resolution, but the approach has some inherent limitations. The algorithm is based on signal processing models that characterize a complex target as a collection of point scatterers, each with its own frequency independent scattering amplitude. Such models are often sufficient for typical wideband signal processing where the waveforms have only a small fractional bandwidth compared to the center frequency. Over ultra-wide bandwidths, i.e. where the radar's bandwidth is comparable to it's center frequency, the scattering amplitude of the individual scattering centers can vary significantly with frequency. Spheres, edges, and surface joins are examples of realistic scattering centers that exhibit significant amplitude variations as a function of frequency.
Measuring or estimating a target's ultra-wideband radar signature is very useful from many radar discrimination and target identification viewpoints. Not only would extremely fine range resolution be obtained, but the amplitude variations of isolated scattering centers would help in typing the scattering center. Many canonical scattering centers are known to exhibit .function..sup..alpha. -type scattering behavior, e.g. the RCS of flat plates, singly curved surfaces (cone sections), and doubly curved surfaces (sphere) vary as .function..sup.2, .function..sup.1, and .function..sup.0, respectively. The RCS of a curved edge varies as .function..sup.-1, whereas, a cone vertex may be characterized with an .function..sup.-2 RCS frequency dependence. One of the goals of UWB processing is to detect these frequency dependent terms in the measured data and to exploit them for scattering type identification.
Fielding a true UWB radar can be very expensive. Accordingly, a need remains for a system and method providing the benefits of ultra-wideband radar without the cost, both monetary and in terms of required bandwidth, of a true ultra-wideband radar.